The Three Hundred: <i>M</i>sub–<i>V</i>circ relation
Bibliographic record
Abstract
ABSTRACT In this study, we investigate a recent finding based on strong lensing observations, which suggests that the sub-haloes observed in clusters exhibit greater compactness compared to those predicted by ΛCDM simulations. To address this discrepancy, we compare the cumulative sub-halo mass function and the Msub–Vcirc relation between observed clusters and 324 simulated clusters from $\rm \small {The\,Three\,\,Hundred}$ project, focusing on the hydrodynamic resimulations using $\rm \small {Gadget-X}$ and $\rm \small {Gizmo-Simba}$ baryonic models. The cumulative sub-halo mass function of $\rm \small {Gizmo-Simba}$ simulated clusters aligns with observations, while $\rm \small {Gadget-X}$ simulations exhibit discrepancies in the lower sub-halo mass range, possibly due to its strong supernova feedback. Both $\rm \small {Gadget-X}$ and $\rm \small {Gizmo-Simba}$ simulations demonstrate a redshift evolution of the sub-halo mass function and the Vcirc function, with slightly fewer sub-haloes observed at lower redshifts. Neither the $\rm \small {Gadget-X}$ nor $\rm \small {Gizmo-Simba}$ (albeit a little closer) simulated clusters’ predictions for the Msub–Vcirc relation align with the observational result. Further investigations on the correlation between sub-halo/halo properties and the discrepancy in the Msub–Vcirc relation reveal that the sub-halo’s half mass radius and galaxy stellar age, the baryon fraction, and sub-halo distance from the cluster’s centre, as well as the halo relaxation state, play important roles on reproducing this relation. Nonetheless, challenges persist in accurately reproducing the observed Msub–Vcirc relationship within our current hydrodynamic cluster simulation that adheres to the standard ΛCDM cosmology. These challenges may stem from shortcomings in our baryon modelling, numerical intricacies within the simulation, or even potential limitations of the ΛCDM framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".